{
  "metadata": {
    "language_info": {
      "codemirror_mode": {
        "name": "python",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8"
    },
    "kernelspec": {
      "name": "python",
      "display_name": "Pyolite",
      "language": "python"
    },
    "colab": {
      "name": "9.ipynb",
      "provenance": []
    }
  },
  "nbformat_minor": 0,
  "nbformat": 4,
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "样本自相关的置信区间"
      ],
      "metadata": {
        "collapsed": false,
        "pycharm": {
          "name": "#%% md\n"
        },
        "id": "HsSn0VOq5RKU"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "此示例说明如何为白噪声过程的自相关序列创建置信区间。创建长度为 L=1000 个采样点的白噪声过程的实现。计算最大滞后为 20 的样本自相关。绘制白噪声过程的样本自相关和大约 95% 的置信区间。\n",
        "\n",
        "创建白噪声随机向量。采用随机数生成器的默认设置，以获得可重现的结果。求出最大滞后为 20 的归一化样本自相关。"
      ],
      "metadata": {
        "collapsed": false,
        "id": "lRI-mhcf5RKW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "from matplotlib import pyplot as plt\n",
        "from scipy.special import erfinv"
      ],
      "metadata": {
        "trusted": true,
        "id": "Wawu9RWa5RKX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "L = 1000\n",
        "x = np.random.randn(L)"
      ],
      "metadata": {
        "trusted": true,
        "id": "8Uh3sP2J5RKX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(x)\n",
        "plt.show()"
      ],
      "metadata": {
        "trusted": true,
        "id": "of2sx3Xx5RKY",
        "outputId": "71355d24-b634-446b-f209-ed254be1930d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<pyolite.display.Image at 0x6d62f08>",
            "image/png": 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"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def autocorrelation(x, lags):\n",
        "    n = len(x)\n",
        "    x = np.array(x)\n",
        "    result = [np.correlate(x[i:],x[:n-i])\\\n",
        "            /(x[i:].std()*x[:n-i].std()*(n-i)) for i in range(0, lags+1)]\n",
        "    lag = np.arange(0, lags+1, 1)\n",
        "    return result, lag"
      ],
      "metadata": {
        "trusted": true,
        "id": "H9ypMXk35RKZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "xc, lags = autocorrelation(x, 20)"
      ],
      "metadata": {
        "trusted": true,
        "id": "Bjk3-1d85RKZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "为正态分布 N(0,1/L) 创建 95% 的上、下置信边界，其标准差为 1/√L。对于 95% 置信区间，临界值是 √2erf<sup>−1</sup>(0.95)≈1.96，置信区间是Δ=0±1.96/√L."
      ],
      "metadata": {
        "id": "ChBj_Y_m5RKa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "vcrit = np.sqrt(2)*erfinv(0.95)\n",
        "print(vcrit)"
      ],
      "metadata": {
        "trusted": true,
        "id": "vWMRvYY75RKa",
        "outputId": "9f83c7b7-afde-4ba3-b916-49db9a3441f5"
      },
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "text": "1.9599639845400545\n",
          "output_type": "stream"
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "lconf = -vcrit/np.sqrt(L)\n",
        "hconf = vcrit/np.sqrt(L)"
      ],
      "metadata": {
        "trusted": true,
        "id": "rgsuWxw85RKa"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "lline = lconf * np.ones(len(lags))\n",
        "hline = hconf * np.ones(len(lags))"
      ],
      "metadata": {
        "trusted": true,
        "id": "EUGLQvEm5RKa"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "绘制样本自相关和 95% 置信区间。"
      ],
      "metadata": {
        "id": "pJHw1MHn5RKb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.stem(lags, xc, 'o')\n",
        "plt.plot(lags, lline, 'g')\n",
        "plt.plot(lags, hline, 'g')\n",
        "plt.ylim([lconf-0.03, 1.05])\n",
        "plt.title('Sample Autocorrelation with 95% Confidence Intervals')\n",
        "plt.show()"
      ],
      "metadata": {
        "trusted": true,
        "id": "vT_Be7Fo5RKb",
        "outputId": "def8aeea-bbfd-41fc-af6e-01ad0c347cb8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<pyolite.display.Image at 0x6e522e0>",
            "image/png": 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"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "从上图中可以看出，唯一位于 95% 置信区间之外的自相关值出现在滞后 0 处，正如白噪声过程所预期的那样。基于此结果，您可以得出结论，该数据是白噪声过程的实现。"
      ],
      "metadata": {
        "id": "pL5hbtXz5RKb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "bYXY6idP5RKb"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}